Non-destructive assessment of the oxidative stability of intact macadamia nuts during the drying process by near-infrared spectroscopy

We have developed a rapid non-destructive method to assess the oxidative stability of intact macadamia nuts using near-infrared spectroscopy (NIRS). Intact macadamia nuts of the cultivars HAES 344 ‘Kau’, HAES 660 ‘Keaau’, IAC 4–12 B, and IAC Campinas B were harvested and immediately oven-dried for 4 days at 30 °C, 2 days at 40 °C, and 1 day at 60 °C to achieve 1.5% kernel moisture content. At each drying step nuts were withdrawn and their moisture content, peroxide value (PV), and acidity index (AI) determined. The best partial least square model for PV prediction was obtained using the Savitzky-Golay (SG) second derivative resulting in a standard error of prediction (SEP) of 0.55 meq·kg−1 and a coefficient of determination (R2C) of 0.57. The best AI prediction-model result was obtained using the SG second derivative (SEP = 0.14%, R2C = 0.29). Based on the maximum quality limits of 3 meq·kg−1 for PV and 0.5% for AI, the SEP values represented 18% and 28%, respectively. Therefore, the prediction method can be considered useful since the errors are lower than the quality limits. Thus, NIRS can be used to assess the oxidative stability of intact macadamia kernels

Determination of relationships and genetic variation among Amorphophallus sp. from northern part of Thailand

Amorphophallu sp. are known under the common name of konjac or elephant foot yam. Some of the species have potential to become highly profitable crops for South East Asia as raw material for various industries. However, considerable variation in morphological features of many species of Amorphophallus makes it is difficult to identify them in the vegetative form. Randomly Amplified Polymorphic DNA (RAPD) and DNA Sequencing are often used to determine the genetic relationship of plants. The aim of this study was to determine the relationship and genetic variation of various accessions of Amorphophallus sp. collected in northern regions of Thailand. Fifty samples were characterised by RAPD with four primers (ERIC1R, ERIC 2, BOXA1R, RPO1) the data from which were used to calculate genetic distances which were then visualized using multidimensional scaling. In addition, the psbM-trnD region of their chloroplast genome was also sequenced from which phylogenetic relationships were determined using parsimony analysis. The results from the RAPD analysis placed the accessions into 35 different groups with distance values between 0.075 and 0.949. The DNA sequence data found the accessions into 30 different groups. Further work will be carried out to more closely determine the relationships between the accessions and to relate them to each other

A soft computing tool for species classification and prediction of glucomannan content in Amorphophallus genus

The proposed work aims at designing a classification system for automatic identification of A. muelleri species, grown as a potential cash crop in many Asian countries, from the DNA fingerprints of Amorphophallus genus. Four sets of 48 DNA fingerprints belonging to 37 species of the Amorphophallus genus, developed with the help of four different primers are considered for the experiment, with an objective to identify only the fingerprints of the species of interest. A second experimental setup deals with the automatic classification of species containing high amounts of glucomannan from the same set of DNA fingerprints of the Amorphophallus genus. For each set of 48 DNA fingerprints generated with a specific primer, the DNA fingerprints are preprocessed to extract a 42 dimensional feature vector which is used to generate a k-Nearest Neighbor based classifier based on the Leave One Out Cross Validation protocol. Final classification based on outputs from individual classifiers constructed with respect to the four different primers is performed according to a n-star consensus strategy. The n-star consensus predicts species A. muelleri with cent per cent accuracy while it predicts species containing glucomannan with a more modest accuracy of 81.25%

Genetic variation among Amorphophallus sp. from Northern Thailand and their glucomannan content

This study investigated the genetic variations among different accessions of Amorphophallus sp. collected in northern regions of Thailand. Forty-tree samples were characterized by RAPD with four primers (ERIC1R, ERIC 2, BOXA1R, RPO1) the data from which were used to calculate genetic distances which were then visualized using multidimensional scaling and cladogram. The psbM-trnD region of their chloroplast genome was also sequenced and phylogenetic relationships were determined using parsimony analysis. In addition, glucomannan content was determined to find the relationship between genetic variation and glucomannan content. The results from the RAPD analysis show that the genetic distance values vary between 0.075 and 0.949 and that A. muelleri can be separated from A. paeoniifolius. However, the separation of the other species was ambiguous. The DNA sequence data suggested the presence of 5 different clades. All genetic data indicated that genetic variation was high. Glucomannan content was between 1.53-65.78% (w/w) depending on the species and the regions of origin. As a result, these markers appear to be suitable for the use as selection tools aiming at improving the industrial production of konjac glucomannan